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I experimented with RL after college and threw together a tic-tac-toe program based on a section in the Sutton and Barto text. I eventually implemented an evolutionary algorithm to generalize from a small number of states. I apologize for the messiness of the code. I put this together during the free time I had between graduating and starting my job (I was actually on a plane the last time I worked on this). I just wanted make a post in case someone finds anything interesting in my approach. The repo can be found here.
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As a civil engineer, Scott Ashford used explosives to make the ground under Japan’s Sendai airport safer in an earthquake. Now, as the dean of the engineering college at Oregon State University, he’s at ground zero of another seismic event. In its biggest fundraising celebration in nearly a decade, Oregon State announced plans today for Read article >
The post AI Supercomputer to Power $200 Million Oregon State University Innovation Complex appeared first on NVIDIA Blog.
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I saw this post on r/MachineLearning about fine-tuning StableDiffusion on a custom dataset and decided to have a go. From a previous project, I had a dataset of images of Mobile Suits (i.e humanoid mechas) from the anime franchise Mobile Suit Gundam.
Project: https://github.com/Askannz/gundam-stable-diffusion (see there for code&data)
Some fun results: https://imgur.com/a/1Bg1Lyy
Colab demo: https://colab.research.google.com/drive/11Bdkub4OGtMNdSlMKx4fklB5LAtFFVpG
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A considerable percentage of new apps in the Google App store are removed for violating the store's guidelines. This is inconvenient for the users of these apps, who may lose their in-app data. Computer scientists from the University of Groningen have devised two machine learning models that can predict the chances of a new app being removed, both before and after uploading it to the app store. These models can help both developers and users. The details of this project are described in a paper that was published in the journal Systems and Soft Computing on Sept. 29.
The Google Play store has set rules and requirements that developers must adhere to. After being submitted, apps are immediately uploaded to the store, but it takes Google some time to vet them before they remove apps that ar…
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A couple of days ago, Stability AI “infiltrated” the r/StableDiffusion community, banned some of the users, kicked out the moderators and took over the subreddit
https://analyticsindiamag.com/when-stability-ai-went-rogue-on-reddit-rampage%ef%bf%bc/
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Amazon SageMaker multi-model endpoint (MME) enables you to cost-effectively deploy and host multiple models in a single endpoint and then horizontally scale the endpoint to achieve scale. As illustrated in the following figure, this is an effective technique to implement multi-tenancy of models within your machine learning (ML) infrastructure. We have seen software as a […]
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This post was co-written with Tobias Wenzel, Software Engineering Manager for the Intuit Machine Learning Platform. We all appreciate the importance of a high-quality and reliable machine learning (ML) model when using autonomous driving or interacting with Alexa, for examples. ML models also play an important role in less obvious ways—they’re used by business applications, […]
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Amazon Neptune ML is a machine learning (ML) capability of Amazon Neptune that helps you make accurate and fast predictions on your graph data. Under the hood, Neptune ML uses Graph Neural Networks (GNNs) to simultaneously take advantage of graph structure and node/edge properties to solve the task at hand. Traditional methods either only use […]
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If you’re like most people, you probably think that only highly intelligent people are capable of being creative. But as it turns out, this…
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(Unlocked bonus post - longggg bonus post!)
What does DALL-E2 generate when I ask it for the most popular Halloween candy of each US state?
Each prompt is included in the picture's caption - you can see that after a while I started varying it a bit, first
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Hi,
I run a startup with three other founders and I have a problem that machine learning and OCR (optical character recognition) would solve. But we are stretched thin and it has been a few years since my CTO - a software architect with nearly 40 years experience - worked on anything similar, so we are unsure if this exercise would pull us away from our core focus too much.
That is why we are looking for someone who is interested in taking on this problem as a project. This is a bounded problem, meaning it is very achievable. We just don't know how long it would take. We are willing to offer equity as part of an model called restricted stock units, so if we are commercially successful you would have a signed agreement from us to claim a nominal amount of shares.
The Problem
This is a s…
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I made a website for a PoC, but currently its not really working well
especially for those images that have some human-like brush styles
https://www.illuminarty.ai/
This started off as a pure hobby based but I started getting a bit of some traction from the art communities (mainly anime), now I am seriously considering if I should start spending more time on this but I lack brain cells
is anyone here interested in this topic? do you think this would be of any use?
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If you're looking for some of the interesting AI chatbot use cases with examples, it's a quick read:
https://www.haptik.ai/blog/conversational-ai-in-apac?utm_source=website&utm_medium=blog&utm_campaign=conversationalAI&utm_content=read+more
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You must have come across matrix multiplication in school textbooks. But did you know how relevant it is in every aspect of our daily lives, from processing images on our phones and recognising speech commands to generating graphics for computer games?
https://analyticsindiamag.com/why-solving-for-efficiency-of-matrix-multiplication-such-a-big-deal-in-computing/
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Amazon SageMaker Pipelines is a continuous integration and continuous delivery (CI/CD) service designed for machine learning (ML) use cases. You can use it to create, automate, and manage end-to-end ML workflows. It tackles the challenge of orchestrating each step of an ML process, which requires time, effort, and resources. To facilitate its use, multiple templates […]
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If you have searched for an item to buy on amazon.com, you have used Amazon Search services. At Amazon Search, we’re responsible for the search and discovery experience for our customers worldwide. In the background, we index our worldwide catalog of products, deploy highly scalable AWS fleets, and use advanced machine learning (ML) to match […]
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When it comes to reimagining the next generation of automotive, NIO is thinking outside the car. This month, the China-based electric vehicle maker introduced its lineup to four new countries in Europe — Denmark, Germany, the Netherlands and Sweden — along with an innovative subscription-based ownership model. The countries join NIO’s customer base in China Read article >
The post Hello, World: NIO Expands Global Footprint With Intelligent Vehicle Experiences appeared first on NVIDIA Blog.
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NVIDIA and Oracle are teaming to make the power of AI accessible to enterprises across industries. These include healthcare, financial services, automotive and a broad range of natural language processing use cases driven by large language models, such as chatbots, personal assistants, document summarization and article completion. Join NVIDIA and Oracle experts at Oracle CloudWorld, Read article >
The post Learn How NVIDIA Advances AI for Enterprises, at Oracle CloudWorld appeared first on NVIDIA Blog.
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Alien invasions. Gritty dystopian megacities. Battlefields swarming with superheroes. As one of Hollywood’s top concept artists, Drew Leung can visualize any world you can think of, except one where AI takes his job. He would know. He’s spent the past few months trying to make it happen, testing every AI tool he could. “If your Read article >
The post Press Art to Continue: New AI Tools Promise Art With the Push of a Button — But Reality Is More Complicated appeared first on NVIDIA Blog.
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High-end PC gaming arrives on more devices this GFN Thursday. GeForce NOW RTX 3080 members can now stream their favorite PC games at up to 1600p and 120 frames per second in a Chrome browser. No downloads, no installs, just victory. Even better, NVIDIA has worked with Google to support the newest Chromebooks, which are Read article >
The post GeForce NOW Streams High-Res, 120-FPS PC Gaming to World’s First Cloud Gaming Chromebooks appeared first on NVIDIA Blog.
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"On average, across 4 NLP tasks and 10 attention types, single layer wide models perform 0.3% better than their deep counterparts"
Discussions of some wide attention results
https://twitter.com/andrey_kurenkov/status/1579474438822985728
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All you have to do is input a YouTube video link and get a video with subtitles (alongside with .txt, .vtt, .srt files).
Whisper can translate 98 different languages to English. If you want to give it a try;
Link of the app: https://huggingface.co/spaces/BatuhanYilmaz/Auto-Subtitled-Video-Generator
https://reddit.com/link/y2cpjc/video/oiac58arcft91/player
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I would like you to give me your opinion and also tell me what could be improved. The video explains in detail the explainable artificial intelligence technique, LIME. The video derives from my bachelor's thesis. Thank you!
Understanding LIME | Explainable AI
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The age of electric vehicles has arrived and, with it, an entirely new standard for premium SUVs. Polestar, the performance EV brand spun out from Volvo Cars, launched its third model today in Copenhagen. With the Polestar 3, the automaker has taken SUV design back to the drawing board, building a vehicle as innovative as Read article >
The post Large and Fully Charged: Polestar 3 Sets New Standard for Premium Electric SUVs appeared first on NVIDIA Blog.
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This week 'In the NVIDIA Studio' creators can now pick up the GeForce RTX 4090 GPU, available from top add-in card providers including ASUS, Colorful, Gainward, Galaxy, GIGABYTE, INNO3D, MSI, Palit, PNY and ZOTAC, as well as from system integrators and builders worldwide.
The post GeForce RTX 4090 GPU Arrives, Enabling New World-Building Possibilities for 3D Artists This Week ‘In the NVIDIA Studio’ appeared first on NVIDIA Blog.
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Original tune melody is a slide guitar. The AI changed that to a human-like voicing.
The AI version is a rough cut but eq and processing cleaned it up a bit.
The AI created whispers throughout as well as changing the slide guitar.
Original
https://soundcloud.com/iamlazerkat/lost-in-the-fabric-of-space-time
AI
https://soundcloud.com/iamlazerkat/ai-voiced-lost-in-the-fabric-of-space-time
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For decades, making a machine fully capable of learning by observing its environment has been the biggest dream for many researchers. Though methods like supervised or reinforcement learning have made huge advancements, there is a lot of speculation if they are the right way forward.
https://analyticsindiamag.com/yann-lecuns-version-of-autonomous-machine-intelligence/
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A massive amount of business documents are processed daily across industries. Many of these documents are paper-based, scanned into your system as images, or in an unstructured format like PDF. Each company may apply unique rules associated with its business background while processing these documents. How to extract information accurately and process them flexibly is […]
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More info at https://outsystems-ai-reading-group.github.io/
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Absolute beginner in model deployment here, looking to build an API endpoint to this model specifically. Most articles I found online are either too simplistic (docker+fastAPI, which is known be very slow for inference from transformers), or they are so complex that it goes over the top of my head.
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Climate Change, as an extension or corollary Energy Transitions, is undoubtedly one of the most critical issues that merit urgent and serious attention from policymakers, scientists, and governments across the globe. However, before looking for solutions, it is equally important to define and frame the problem in the most realistic and unbiased way to ensure the holistic nature of the solution(s).
The post Energy Transitions: We Need To Redefine the Problem and Reframe the Narrative appeared first on Data Science Central.
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In Part 1 of the “Building Blocks for Modern Data Management”, I explored two important modern data management concepts: Data Subassemblies and Data Products (Figure 1). Data Subassemblies are the packaging and pre-wiring of data and its supporting accouterments (e.g., enriched metadata, data access methods, data governance policies and procedures, data access security protocols, data… Read More »Data Subassemblies and Data Products Part 2: Economics and Journey Maps
The post Data Subassemblies and Data Products Part 2: Economics and Journey Maps appeared first on Data Science Central.
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The issue is not just the actual multiplication but the fastest method to perform the multiplication. The speeding up of matrix multiplication calculations has a high impact because matrix multiplication is a part of many applications - especially in deep learning and image processing.
The post AlphaTensor and Its Implications for AI, Reinforcement Learning, and Science appeared first on Data Science Central.
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Use cases for ML are seemingly infinite, from automatic responses to queries and automated stock trading, to recommendation engines and customer experience enhancements
The post Declarative Machine Learning Alone isn’t Enough for the Data Science Community appeared first on Data Science Central.
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Enterprises often deal with large volumes of IT service requests. Traditionally, the burden is put on the requester to choose the correct category for every issue. A manual error or misclassification of a ticket usually means a delay in resolving the IT service request. This can result in reduced productivity, a decrease in customer satisfaction, […]
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This article is part of a series please read The Marvellous Link first to get a better understanding.
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Automatic subtitle translate and dubbing on YouTube from English to Russian using computer vision
medium article: https://medium.com/@wb-08/automatic-subtitles-dubbing-on-youtube-using-computer-vision-35ad776ffe18
github repo: https://github.com/wb-08/SubVision
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In this post, we present a solution that combines rich mobile device intelligence with customized machine learning (ML) modeling to help you catch fraudsters who exploit mobile apps. GrabDefence (GD), Grab’s proprietary fraud detection and prevention technology, and AWS have launched GDxAFD, a fraud detection solution tailored for mobile apps that integrates GD’s device intelligence […]
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Automated outbound calls are the preferred method of interaction with clients. We have all received an automated call and they will try to sell us something. When handled properly, these calls can enhance customer experience and boost productivity at your company. All you require is the appropriate outbound automated calling solution. These tools take every… Read More »How Automatic Outbound Calling is Important for Small Businesses
The post How Automatic Outbound Calling is Important for Small Businesses appeared first on Data Science Central.
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Source: Unsplash When starting any business, the first step is to create a business plan. A business plan is a document that outlines your business goals and how you plan to achieve them. For a coworking space, you will want to focus on specific aspects of your business when creating your plan. This blog post… Read More »How to write a profitable business plan for a coworking business
The post How to write a profitable business plan for a coworking business appeared first on Data Science Central.
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Back in 2018, BERT got people talking about how machine learning models were learning to read and speak. Today, large language models, or LLMs, are growing up fast, showing dexterity in all sorts of applications. They’re, for one, speeding drug discovery, thanks to research from the Rostlab at Technical University of Munich, as well as Read article >
The post Beyond Words: Large Language Models Expand AI’s Horizon appeared first on NVIDIA Blog.
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Evaluation is a main part for any project, in Biometric system there are a some special evaluation parts used for security reasons and…
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I am trying to calculate the Syntactic divergence for my private Question Answering dataset, but I couldn't find any good implementation or explanation on how to do it in Python.
While Searching, I found This [GitHub script][1] and [this script][2] but couldn't understand the code. Could someone provide a neat example in Python of how to calculate the Syntactic divergence for a custom question-answering dataset?
[1]: https://github.com/Lallivero/qna/blob/master/src/analysis/qa_analysis.py
[2]: https://github.com/Lallivero/qna/blob/10c1106b019dcf0536785db0556f98241da04119/src/dataset_stat/analyze_dep_path.py
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Using Red Hat OpenShift Data Science to create a fully supported sandbox in which to rapidly develop, train, and test machine learning (ML) models in the public cloud before deploying in production.
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Hi r/reinforcementlearning
I wrote a short blog post about the recent paper on Matrix Multiplication. I curate some expert opinions from twitter and give a breakdown of the Tensor trick used in the paper.
https://sudeepraja.github.io/MatrixMultiplication/
I appreciate all corrections and feedback.
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Hi r/MachineLearning
I wrote a short blog post about the recent paper on Matrix Multiplication. I curate some expert opinions from twitter and give a breakdown of the Tensor trick used in the paper.
https://sudeepraja.github.io/MatrixMultiplication/
I appreciate all corrections and feedback.
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singularity - is a hypothetical point in time at which technological growth will become radically faster and uncontrollable, resulting in unforeseeable changes to human civilization .
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Last week we launched a Kaggle competition on imputing missing data https://www.kaggle.com/competitions/genentech-404-challenge/overview. The challenge: handling different data missingness patterns in an automatic way.
The development data consisting of a complete tabular dataset along with three missingness masks meant to simulate different patterns of missing data.
Two test sets are released and each test set has a different, unspecified missingness mechanism. The public leaderboard includes 20% of each test set and the private leaderboard includes the remaining 80% of each test set.
Hope everyone has a great weekend.
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The problem: https://i.imgur.com/mTsrpYM.png
The problem's question: https://i.imgur.com/qX6xmyi.png
I have no idea how to go about this. How do I go about constructing an admissible heuristic for this sliding tile game problem?
Please let me know how and how to go about with the explanation. I'm a bit confused here. Guidance would be appreciated, thanks.
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Posted it on stackexchange, I might as well post the link here in case someone has had a similar experience:
https://ai.stackexchange.com/questions/37288/tensorflow-set-weights-and-get-weights-are-too-slow
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If you're wondering about this, come and participate in two amazing weeks (21 Oct ~ 5 Nov) of Quantum hackathon HAQS with code, workshops, fun and prizes, organized by qBraid which will consist of a leaderboard for a Quantum Machine Learning challenge. Save your spot here: https://account.qbraid.com/haqs
https://preview.redd.it/vetyrpx7x8s91.png?width=1080&format=png&auto=webp&s=02f5aeb767b2ddfe4a3efb8dfc2e00896c1bade7
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Video demo: https://www.youtube.com/watch?v=qy2MrNhsoIs
Project page: https://github.com/Aubrey-ao/HumanBehaviorAnimation
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Greater availability of de-identified patient health data would enable better treatments and diagnostics, the researchers say.
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Synamedia is a leading video technology provider addressing the needs for premium video service providers and direct-to-consumer (D2C) with a comprehensive solution portfolio. Synamedia solutions spread across several pillars such as video networks, TV platforms, advertisement and monetization, and content protection and piracy disruption. Synamedia partnered with AWS to use artificial intelligence (AI) to develop […]
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Model training forms the core of any machine learning (ML) project, and having a trained ML model is essential to adding intelligence to a modern application. A performant model is the output of a rigorous and diligent data science methodology. Not implementing a proper model training process can lead to high infrastructure and personnel costs […]
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This post was co-written with Robert Berger and Adine Deford from InformedIQ. InformedIQ is the leader in AI-based software used by the nation’s largest financial institutions to automate loan processing verifications and consumer credit applications in real time per the lenders’ policies. They improve regulatory compliance, reduce cost, and increase accuracy by decreasing human error […]
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Shared our methodology for successful Computer Vision projects. Check it out!
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Cooler weather, the changing colors of the leaves, the needless addition of pumpkin spice to just about everything, and discount Halloween candy are just some things to look forward to in the fall. GeForce NOW members can add one more thing to the list — 25 games joining the cloud gaming library in October, including Read article >
The post Fall Into October With 25 New Games Streaming on GeForce NOW appeared first on NVIDIA Blog.
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https://lambdalabs.com/blog/inference-benchmark-stable-diffusion/
This inference benchmark of Stable Diffusion analyzes how different choices in hardware (GPU model, GPU vs CPU) and software (single vs half-precision, PyTorch vs ONNX runtime) affect inference performance in terms of speed, memory consumption, throughput, and quality of the output images.
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Last week I decided to run a simple experiment to with the new SetFit method developed by teams at Hugging Face, Intel Labs and UKP Lab.
What results can I get by spending some time labeling a few, but good quality examples of the unlabeled split of the IMDb benchmark dataset?
I was actually very impressed with the generalisation capacity of SetFit so I decided to write the tutorial below.
I think it also shows that taking some time to label good quality data can give you strong results thanks to the representation capabilities of current models.
I'd love to hear your thoughts!
https://rubrix.readthedocs.io/en/master/tutorials/few-shot-classification-with-setfit.html
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https://www.nature.com/articles/s41586-022-05172-4
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"A self-programming AI implemented using a code generation model can successfully modify its own source code to improve performance and program sub-models to perform auxiliary tasks."
Twitter discussion: https://twitter.com/nearcyan/status/1576620734146756609
Another discussion in r/singularity: https://www.reddit.com/r/singularity/comments/xtwd7k/selfprogramming_artificial_intelligence_using/
ICLR OpenReview: https://openreview.net/forum?id=SKat5ZX5RET
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Digital is the new normal, and there’s no going back. Every year, consumers visit, on average, 191 websites or services requiring a user name and password, and the digital footprint is expected to grow exponentially. So much exposure naturally brings added risks like account takeover (ATO). Each year, bad actors compromise billions of accounts through […]
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Content moderation is the process of screening and monitoring user-generated content online. To provide a safe environment for both users and brands, platforms must moderate content to ensure that it falls within preestablished guidelines of acceptable behavior that are specific to the platform and its audience. When a platform moderates content, acceptable user-generated content (UGC) […]
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Face-off Probability is the National Hockey League’s (NHL) first advanced statistic using machine learning (ML) and artificial intelligence. It uses real-time Player and Puck Tracking (PPT) data to show viewers which player is likely to win a face-off before the puck is dropped, and provides broadcasters and viewers the opportunity to dive deeper into the […]
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Thanks to earbuds, people can take calls anywhere, while doing anything. The problem: those on the other end of the call can hear all the background noise, too, whether it’s the roommate’s vacuum cleaner or neighboring conversations at a café. Now, work by a trio of graduate students at the University of Washington, who spent Read article >
The post Researchers Use AI to Help Earbud Users Mute Background Noise appeared first on NVIDIA Blog.
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When not engrossed in his studies toward a Ph.D. in statistics, conducting data-driven research on AI and robotics, or enjoying his favorite hobby of sailing, Yizhou Zhao is winning contests for developers who use NVIDIA Omniverse — a platform for connecting and building custom 3D pipelines and metaverse applications.
The post Meet the Omnivore: Ph.D. Student Lets Anyone Bring Simulated Bots to Life With NVIDIA Omniverse Extension appeared first on NVIDIA Blog.
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Julien Salinas wears many hats. He’s an entrepreneur, software developer and, until lately, a volunteer fireman in his mountain village an hour’s drive from Grenoble, a tech hub in southeast France. He’s nurturing a two-year old startup, NLP Cloud, that’s already profitable, employs about a dozen people and serves customers around the globe. It’s one Read article >
The post AI Esperanto: Large Language Models Read Data With NVIDIA Triton appeared first on NVIDIA Blog.
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Over the years, I’ve hosted many AI & emerging tech events and there’s one question that comes up a lot. Do I need to be an engineer or…
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Until the last decade, software development was a new chapter in the history of enterprise evolution. However, with time, the industry has…
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Machine Learning and Data Science are two terms that have become very popular over the past few years. It is important to understand that…
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Artificial intelligence (AI) has the potential to change our society, but it also raises ethical questions. The use of AI in healthcare is…
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In Part 7.0 of the Transfer Learning series we have discussed about Densenet pre-trained model in depth so in this series we will…
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Who are the most successful PhD researchers? Or more precisely people who achieved the most (in terms of citations, impact etc.) while being PhD students? If you can give examples in last say 50 years but also more recent ones say last 5 years.
Someone I noticed: Chelsea Finn
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I have a Python program which captures a pair of stereo rectified images, and I'd like to use this model to generate the disparity map. I'm unfamiliar with TensorRT and TAO, so am looking for either a high-level explanation of how it would be possible to use the model for inference within my program, or instruction on how to do so.
https://catalog.ngc.nvidia.com/orgs/nvidia/teams/isaac/models/dnn_stereo_disparity
Thanks in advance!
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More info at https://outsystems-ai-reading-group.github.io/
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I have asked this question about off-policy learning, in THE book (Sutton & Barto). I didn't get any replies on ai.stackechange, so I am also posting it here. I would be thankful if you could help me out. Thank you.
https://ai.stackexchange.com/questions/37258/off-policy-monte-carlo-learning-why-is-probability-of-sampling-a-trajectory-the
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Near-real-time delivery of data and insights enable businesses to rapidly respond to their customers’ needs. Real-time data can come from a variety of sources, including social media, IoT devices, infrastructure monitoring, call center monitoring, and more. Due to the breadth and depth of data being ingested from multiple sources, businesses look for solutions to protect […]
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Creating robust and reusable machine learning (ML) pipelines can be a complex and time-consuming process. Developers usually test their processing and training scripts locally, but the pipelines themselves are typically tested in the cloud. Creating and running a full pipeline during experimentation adds unwanted overhead and cost to the development lifecycle. In this post, we […]
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TwitchCon — the world’s top gathering of live streamers – kicks off Friday with the new line of GeForce RTX 40 Series GPUs bringing incredible new technology — from AV1 to AI — to elevate live streams for aspiring and professional Twitch creators alike.
The post Creator EposVox Shares Streaming Lessons, Successes This Week ‘In the NVIDIA Studio’ appeared first on NVIDIA Blog.
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The trendiest fashion styles are just in! And they’re just one click away with the help of the latest DALL-E deep learning model!
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One-shot and few-shot learning’s Siamese network implementation in Keras
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https://ai.facebook.com/blog/gpu-inference-engine-nvidia-amd-open-source/?utm_source=twitter&utm_medium=organic_social&utm_campaign=blog
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tl;dr - launching Deep Lake - the data lake for deep learning applications
Hey r/ML,
Davit here from team Activeloop. My team and I have worked for over three years on our product, and we're excited to launch the latest, most performant iteration, Deep Lake.
Deep Lake is the data lake for deep learning applications. It retains all the benefits of a vanilla data lake, with one difference. Deep Lake is optimized to store complex data, such as images, videos, annotations, embeddings, & tabular data, in the form of tensors and rapidly streams the data over the network to (1) our lightning-fast query engine: Tensor Query Language, (2) in-browser visualization engine, and (3) deep learning frameworks without sacrificing GPU utilization.
YouTube demo
Detailed Launch post
Key features
A s…
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(Thank you to everyone who participated!) Some of the added features are:
support for dataset poisoning detection for classification models (Spectral Signature Detection)
support for several defenses (Gaussian Noise, Gaussian Augmentation, Reverse Sigmoid)
support for the Kitti dataset format
attacks and visualization for depth perception tasks
webhook functionality to enable easy workflow automation
performance improvement and more.
If you haven't tested it so far, you can make an account and test out the updated version. Your feedback is really appreciated. You can sign up here https://www.navinfo.eu/services/cybersecurity/guardai/ and leave your feedback directly through the platform. Thank you!
GuardAI
We harness the power of AI and Cybersecurity to develop more secure and robust solutions.
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Automatic subtitle translate and dubbing on YouTube from English to Russian using computer vision:
https://reddit.com/link/xuhd46/video/flfr15ezxkr91/player
Subtitle recognition video demo: https://www.youtube.com/watch?v=Y9OAd61ihJQ
Github Repo: https://github.com/wb-08/SubVision
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Check out the real-life examples of machine learning in healthcare, benefits of implementing AI/ML and things to consider before implementing ML in healthcare. https://itchronicles.com/artificial-intelligence/how-machine-learning-in-healthcare-10-real-business-cases/
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Hi I'm looking for any multiagent payload transport environments publicly available for experimentation, like the one shown in here https://youtu.be/7gE_n6b5-LM
Any similar environments where the agents are required to collectively act to transport an object are very much appreciated. TIA.
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Machine learning (ML) has improved business across industries in recent years—from the recommendation system on your Prime Video account, to document summarization and efficient search with Alexa’s voice assistance. However, the question remains of how to incorporate this technology into your business. Unlike traditional rule-based methods, ML automatically infers patterns from data so as to […]
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This post is a joint collaboration with Andries Engelbrecht and James Sun of Snowflake, Inc. The cloud computing revolution has enabled businesses to capture and retain corporate and organizational data without capacity planning or data retention constraints. Now, with diverse and vast reserves of longitudinal data, companies are increasingly able to find novel and impactful […]
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Amazon Elastic Compute Cloud (Amazon EC2) G5 instances are the first and only instances in the cloud to feature NVIDIA A10G Tensor Core GPUs, which you can use for a wide range of graphics-intensive and machine learning (ML) use cases. With G5 instances, ML customers get high performance and a cost-efficient infrastructure to train and […]
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The future of artificial intelligence in third world countries is one of the most important topics to be discussed today. For decades…
( 10
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Python is a popular programming language with many advantages over other languages. It’s easy to read, write and maintain, which makes it the perfect choice for beginners and experts alike. There are lots of libraries available for almost any type of data science you could want to do and it has great documentation. Plus, there's an incredible community that's always happy to answer your questions or give you advice on how to get started!
The post 10 Reasons to Choose Python for Your Next Web Development Project appeared first on Data Science Central.
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I believe that there are two key modern data management “products” required to transition data management into a business discipline focused on helping organizations accelerate their data-driven business innovation. One of those “products” – Data Products – is already gaining wide acceptance as a way for organizations to monetize their customer, product, service, and operational insights or predicted behavioral and performance propensities.
The post Building Blocks for Modern Data Management: Data Subassemblies and Data Products – Part 1 appeared first on Data Science Central.
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At first impression, humanoid robots do not have much in common with autonomous cars. But both are autonomous devices. Hence, lessons learned in creating autonomous cars could be applied to developing autonomous robots.
The post Tesla’s Optimus: Humanoid robots before autonomous cars? appeared first on Data Science Central.
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Hello,
I wanted to try on technique of reinforcement learning for music generation / imitation:
It learns the first few notes after say a few hundred episodes but then somehow it gets stuck and can not learn the whole piece:
https://github.com/githubuser1983/music_generation_with_reinforcement_learning
Here is some result, after playing a little bit with some hyperparameters:
pdf: https://drive.google.com/file/d/1dB-gc7BPev4cryVbiDFTyBm0qKCGnhq8/view?usp=sharing
mp3: https://drive.google.com/file/d/1VF7HUonfQXAVSzMANgu26fBvZCrFCOYQ/view?usp=sharing
Any feedback would be very nice! (I am not sure what the right flair is for this post)
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Are machines still dreaming of electrical sheep? Or have they moved on to replace human workers?
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blue stability, fork of stability-sdk, adds a bash cli for checkpointing and automation, like this script:
blue_stability text_to_video \ https://www.gutenberg.org/cache/epub/51833/pg51833.txt \ url,~dryrun,frame_count=100,marker=PART \ --seed 43 \ --start_schedule 0.9
https://i.redd.it/awefb97wr8r91.gif
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Be our guest as we celebrate 20 years of AI/ML innovation on October 25, 2022, 9:00 AM – 10:30 AM PT. The first 1,500 people to register will receive $50 of AWS credits. Register here. Over the past 20 years, Amazon has delivered many world firsts for artificial intelligence (AI) and machine learning (ML). ML […]
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AWS Panorama is a collection of machine learning (ML) devices and a software development kit (SDK) that brings computer vision to on-premises internet protocol (IP) cameras. AWS Panorama device options include the AWS Panorama Appliance and the Lenovo ThinkEdge SE70, powered by AWS Panorama. These device options provide you choices in price and performance, depending […]
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In this post, we demonstrate how Kubeflow on AWS (an AWS-specific distribution of Kubeflow) used with AWS Deep Learning Containers and Amazon Elastic File System (Amazon EFS) simplifies collaboration and provides flexibility in training deep learning models at scale on both Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon SageMaker utilizing a hybrid architecture approach. […]
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Pressing or pressure in football is a process in which a team seeks to apply stress to the opponent player who possesses the ball. A team applies pressure to limit the time an opposition player has left to make a decision, reduce passing options, and ultimately attempt to turn over ball possession. Although nearly all […]
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Ten years from now, the technological fitness of clubs will be a key contributor towards their success. Today we’re already witnessing the potential of technology to revolutionize the understanding of football. xGoals quantifies and allows comparison of goal scoring potential of any shooting situation, while xThreat and EPV models predict the value of any in-game […]
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Depending on the quality and complexity of data, data scientists spend between 45–80% of their time on data preparation tasks. This implies that data preparation and cleansing take valuable time away from real data science work. After a machine learning (ML) model is trained with prepared data and readied for deployment, data scientists must often […]
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Scott at Astral Codex Ten claims that he already won his bet on the accuracy/quality of image generation models given the current capabilities of Imagen — so I ran a series of human feedback tests to evaluate his victory claim more rigorously.
Blog: https://www.surgehq.ai/blog/dall-e-vs-imagen-and-evaluating-astral-codex-tens-3000-ai-bet
Curious for all of your opinions as well — do Scott's images pass muster?
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I’m creating music with OpenAI Jukebox (link), and the results are full of non-standard noises, which don’t succumb to usual denoising filters.
So my idea was to create a relatively small (10–20 examples) set of non-noisy audio (real music) together with the same audio put through Jukebox (without any AI generation, just conversion).
Then I would need some neural net to “back train” to remove that kind of noise.
Do you think this is doable? If so, is there any Colab or Python library available for this?
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We (KerasCV) launched the world's most performant stable diffusion inference pipeline (as of September 2022). You can assemble it in three lines of code:

keras.mixed_precision.set_global_policy("mixed_float16") model = keras_cv.models.StableDiffusion(jit_compile=True)
Check it out!
https://keras.io/guides/keras_cv/generate_images_with_stable_diffusion/
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I have been looking for a framework/library that can be like/smiliar to PyTorch Lightning. I even checked on Awesome-Jax. Do we have any framework but for Jax/flax/haiku?
I mostly need features: Checkpoint saving, reproducibility, and logging.
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With customer demands growing, regulations around health and safety and net zero increasing, and existing infrastructure aging with each…
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Automation has taken much of the business world by storm. For a good reason, it presents the digital transformation journey transition…
( 10
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Artificial Intelligence and blockchain have been two of the most promising technologies in recent years. They are still waiting to be fully…
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Salesforce.com, the BEST software company in the world.
Continue reading on Becoming Human: Artificial Intelligence Magazine »
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(Thank you to everyone who participated!) Some of the added features are:
support for dataset poisoning detection for classification models (Spectral Signature Detection)
support for several defenses (Gaussian Noise, Gaussian Augmentation, Reverse Sigmoid)
support for the Kitti dataset format
attacks and visualization for depth perception tasks
webhook functionality to enable easy workflow automation
performance improvement and more.
If you haven't tested it so far, you can make an account and test out the updated version. Your feedback is really appreciated. You can sign up here https://www.navinfo.eu/services/cybersecurity/guardai/ and leave your feedback directly through the platform. Thank you!
GuardAI
We harness the power of AI and Cybersecurity to develop more secure and robust solutions.
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Hey, I want to share a podcast with you that I found recently. They try to debunk a popular myth about machines only learning from large amounts of data, and share a use case of applying ML with a small dataset.
What do you think about it?
https://youtu.be/ZVen_YiGcuc
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Sorry for asking another question Dueling Deep Q Networks. I think this paper is a tad bit more confusing than the usual. https://ai.stackexchange.com/q/37234/31755
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Facebook's blog post: https://ai.facebook.com/blog/generative-ai-text-to-video/
Project URL: https://makeavideo.studio/
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Text-Generator.io now pulls down and analyses images with text in them (as well as links and other types of images)
https://text-generator.io/blog/document-question-answering
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The Myosuite challenge (https://sites.google.com/view/myochallenge) at NeurIPS2022 tests our ability to build and train policies for contact-rich manipulation skills.
EvoTorch (evotorch.ai) makes it straightforward to apply evolutionary reinforcement learning to the challenge. We've included setup help, training and visualisation scripts, a baseline controller trained through the provided script and help for submission to the competition. Simply head to the public GitHub to get started: https://github.com/nnaisense/evotorch-myosuite-starter
If you need any more help getting started, come talk to us on our slack
Here's a video of the baseline controller that we've included:
https://reddit.com/link/xqtyw6/video/10qwrq795pq91/player
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This post is co-authored by Salma Taoufiq and Harini Kannan from Sophos. As a leader in next-generation cybersecurity, Sophos strives to protect more than 500,000 organizations and millions of customers across over 150 countries against evolving threats. Powered by threat intelligence, machine learning (ML), and artificial intelligence from Sophos X-Ops, Sophos delivers a broad and […]
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NVIDIA artists ran their engines at full throttle for the stunning Racer RTX demo, which debuted at last week’s GTC keynote, showcasing the power of NVIDIA Omniverse and the new GeForce RTX 4090 GPU. “Our goal was to create something that had never been done before,” said Gabriele Leone, creative director at NVIDIA, who led Read article >
The post The Wheel Deal: ‘Racer RTX’ Demo Revs to Photorealistic Life, Built on NVIDIA Omniverse appeared first on NVIDIA Blog.
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It’s good to be a GeForce NOW member. Genshin Impact’s new Version 3.1 update launches this GFN Thursday, just in time for the game’s second anniversary. Even better: GeForce NOW members can get an exclusive starter pack reward, perfect for their first steps in HoYoverse’s open-world adventure, action role-playing game. And don’t forget the nine Read article >
The post All This and Mor-a Are Yours With Exclusive ‘Genshin Impact’ GeForce NOW Membership Reward appeared first on NVIDIA Blog.
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https://openai.com/blog/dall-e-now-available-without-waitlist/
It appears to work as advertised, not any special workflow. (as a bonus, it does work with organizations too, with credits shared)
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Data-centric approach of building AI models is about focusing as diligently on the data as AI engineers usually do on the models and algorithms. Read more about it here - https://www.artiba.org/blog/data-centric-ai-vs-model-centric-ai-everything-you-need-know
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Thank you to everyone who participated!) Some of the added features are:
support for dataset poisoning detection for classification models (Spectral Signature Detection)
support for several defenses (Gaussian Noise, Gaussian Augmentation, Reverse Sigmoid)
support for the Kitti dataset format
attacks and visualization for depth perception tasks
webhook functionality to enable easy workflow automation
performance improvement and more.
If you haven't tested it so far, you can make an account and test out the updated version. Your feedback is really appreciated. You can sign up here https://www.navinfo.eu/services/cybersecurity/guardai/ and leave your feedback directly through the platform. Thank you!
GuardAI
We harness the power of AI and Cybersecurity to develop more secure and robust solutions.
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Several machine learning models, as neural networks, are very popular in the data science community, due to its scalability and capacity…
Continue reading on Becoming Human: Artificial Intelligence Magazine »
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The rise of artificial intelligence technologies enables organizations to adopt and improve self-service capabilities in contact center operations to create a more proactive, timely, and effective customer experience. Voice bots, or conversational interactive voice response systems (IVR), use natural language processing (NLP) to understand customers’ questions and provide relevant answers. Businesses can automate responses to […]
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As businesses and IT leaders look to accelerate the adoption of machine learning (ML), there is a growing need to understand spend and cost allocation for your ML environment to meet enterprise requirements. Without proper cost management and governance, your ML spend may lead to surprises in your monthly AWS bill. Amazon SageMaker is a […]
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New users can start creating straight away. Lessons learned from deployment and improvements to our safety systems make wider availability possible.
Sign up
Starting today, we are removing the waitlist for the DALL·E beta so users can sign up and start using it immediately. More than 1.5M
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NVIDIA artist Sabour Amirazodi demonstrates his video editing workflows featuring AI this week in a special edition of In the NVIDIA Studio.
The post Video Virtuoso Sabour Amirazodi Shares AI-Powered Editing Tips This Week ‘In the NVIDIA Studio’ appeared first on NVIDIA Blog.
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Source: Unsplash If you’re a coworking space owner and using CRM system, you know that keeping track of your members can be daunting. From juggling monthly membership payments to track who’s been using the printers lately, it’s easy for things to slip through the cracks. That’s where a CRM system comes in handy! Here are… Read More »7 convincing reasons why your coworking needs a CRM system
The post 7 convincing reasons why your coworking needs a CRM system appeared first on Data Science Central.
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Today, data has evolved into one of the most crucial resources in the world. Unlike tangible resources like wood and fuel, the same data set can be used repeatedly and for different applications. Tons of user information gets observed or generated by tech and algorithms to facilitate the personalization we see today.
The post Data Erasure: How to Remove your Information from the Internet? appeared first on Data Science Central.
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Just released a new way to create synthetic media using AI Voices. Speech-to-Speech by Resemble AI will allow you to control your AI voice with any audio file/mic input you provide it with. Here's a quick video showing how it works:
https://youtu.be/cXtgdsWw1xI
https://www.resemble.ai/speech-to-speech/
https://preview.redd.it/btxe8w0vegq91.png?width=2560&format=png&auto=webp&s=f54f791edc4d1a5b0b330932c9deacd1f75e645d
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Tested on Nvidia A10G, took 15-20 mins to train. We can finally run on colab notebooks.
Colab: https://colab.research.google.com/github/ShivamShrirao/diffusers/blob/main/examples/dreambooth/DreamBooth\_Stable\_Diffusion.ipynb
Code: https://github.com/ShivamShrirao/diffusers/blob/main/examples/dreambooth/
More details https://github.com/huggingface/diffusers/pull/554#issuecomment-1259522002
https://preview.redd.it/y19vz2ecpeq91.png?width=949&format=png&auto=webp&s=8e5c8f0bf0b4b6dd1ae92fb6df5713d9bb094096
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The CCPA entitles consumers to know what personal information is being collected and how it is further shared to be used by third parties. Moreover, it is well within the consumers’ rights to stop any business from sharing their data and remove it completely.
The post 7 Key Steps to Comply with California Consumer Privacy Act (CCPA) appeared first on Data Science Central.
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The Cloud has been a dominant paradigm over the last decade but is now attracting regulatory scrutiny.
The post Cloudy Skies: The Rise of Federated Containers and Scrutiny appeared first on Data Science Central.
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The IOT security product industry promises to become a safe road for digital commercialization. IOT security products safeguard networks and interconnected devices. It caters to various business needs such as data encryption, authentication and subsequent, regulatory compliance.
The post Internet of Things Security: Safeguarding Connected Devices and Networks in IoT Era appeared first on Data Science Central.
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In 1974, two distinct but interestingly similar milestones were achieved that would greatly affect the lives of data engineers: the Rubik’s Cube was invented, and IBM released the first relational database. Since its original rise in the 1980s, the Rubik’s Cube has become the world’s most popular puzzle toy.
The post The Similarities of Solving Data Problems and Rubik’s Cubes appeared first on Data Science Central.
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Blockchain experts are in demand. Due to its multiple uses, it needs people handling this new technology. Like any other great profession, these aren't for everyone. You must have or acquire talents by becoming a certified blockchain professional and give reasons to recruiters to hire you.
The post What Careers are Available After Blockchain Certifications? appeared first on Data Science Central.
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A few months ago, Pakistan also faced one of the worst heatwaves in the world, with at one stage, the top 5 of the ten hottest places on earth were in Pakistan.
The post Pakistan Serves As a Great Reminder for Climate Justice appeared first on Data Science Central.
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Before embarking on the data profiling exercise, an analyst must prepare by going through a data profiling analysis.
The post 10 steps to data profiling for successful data discovery: Part II appeared first on Data Science Central.
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I love this infographic recently floating around LinkedIn. Sorry, don’t know to whom to give credit, but it does provide an interesting depiction of how senior management thinks AI works and the realities of what’s required to make AI work.
The post Point – Counterpoint on Why Organizations Suck at AI appeared first on Data Science Central.
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Organizations must opt for a more centralized approach to automate their privacy functions to reduce risk and build transparency and trust with their consumers.
The post Privacy Center: The Key to Meeting Data Privacy Obligations appeared first on Data Science Central.
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Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. Valuable data in organizations is stored in both structured and unstructured repositories. An enterprise search solution should […]
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The proliferation of machine learning (ML) across a wide range of use cases is becoming prevalent in every industry. However, this outpaces the increase in the number of ML practitioners who have traditionally been responsible for implementing these technical solutions to realize business outcomes. In today’s enterprise, there is a need for machine learning to […]
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Amazon SageMaker Pipelines allows data scientists and machine learning (ML) engineers to automate training workflows, which helps you create a repeatable process to orchestrate model development steps for rapid experimentation and model retraining. You can automate the entire model build workflow, including data preparation, feature engineering, model training, model tuning, and model validation, and catalog […]
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Data scientists often train their models locally and look for a proper hosting service to deploy their models. Unfortunately, there’s no one set mechanism or guide to deploying pre-trained models to the cloud. In this post, we look at deploying trained models to Amazon SageMaker hosting to reduce your deployment time. SageMaker is a fully […]
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A machine-learning method finds patterns of health decline in ALS, informing future clinical trial designs and mechanism discovery. The technique also extends to Alzheimer’s and Parkinson’s.
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The MIT-Pillar AI Collective will cultivate prospective entrepreneurs and drive innovation.
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https://github.com/huggingface/diffusers/pull/554#issuecomment-1258751183
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An analysis of TikTok subscriber count. It appears this quantity is highly predictable, and one of the strongest signals is the face of the owner of the channel: https://medium.com/@enryu9000/lookism-in-tiktok-3def0f20cf78
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Useful Tools and Resources for learning about Neuromorphic Computing.
Table of Contents
Getting Started with Neuromorphic Computing
Developer Resources
Online Training Courses
Books
YouTube videos
Neuromorphic Computing Tools, Libraries, and Frameworks
Machine Learning
Deep Learning Development
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Aleksander Madry, Asu Ozdaglar, and Luis Videgaray, co-chairs of the AI Policy Forum, discuss key issues facing the AI policy landscape today.
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Today, we’re excited to announce self-service quota management support for Amazon Textract via the AWS Service Quotas console, and higher default service quotas in select AWS Regions. Customers tell us they need quick turnaround times to process their requests for quota increases and visibility into their service quotas so they may continue to scale their […]
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AI systems are becoming increasingly complex as we move from visionary research to deployable technologies such as self-driving cars, clinical predictive models, and novel accessibility devices. Unlike singular AI models, it is more difficult to assess whether these more complex AI systems are performing consistently and as intended to realize human benefit. How do we […]
The post Assessing AI system performance: thinking beyond models to deployment contexts appeared first on Microsoft Research.
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Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.
For more details: https://github.com/ahmetoner/whisper-asr-webservice
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https://youtu.be/ptsxyD8e4CA
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Neuroscience PhD student Fernanda De La Torre uses complex algorithms to investigate philosophical questions about perception and reality.
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We got close to 50% speedup on A6000 by replacing most of cross attention operations in the U-Net with flash attention
Annotated Implementation: https://nn.labml.ai/diffusion/stable_diffusion/model/unet_attention.html#section-45
Github: https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/master/labml_nn/diffusion/stable_diffusion/model/unet_attention.py#L192
We used this to speed up our stable diffusion playground: promptart.labml.ai
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Here’s the masters program if anyone was curious
https://www.mitropolitiko.edu.gr/en/programmes-of-study/faculty-of-computing/msc-artificial-intelligence/
Thanks
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By taking a proactive approach to cybersecurity, IT departments can help protect their organizations from the ever-growing number of cyber attacks. Here are nine ways IT departments can do proactive cybersecurity.
The post 9 Ways IT Can Do Proactive Cybersecurity appeared first on Data Science Central.
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The leading cancer mortality globally is Lung Cancer. A key objective for increasing lung cancer survival is discovering the illness early, allowing for the most effective treatment choices. Lung cancer develops from lesions in the bronchial epithelium of the lung mucosa. These bronchial lesions can progress to squamous cell lung cancer and assist in forecasting other lung cancers’ development. As a result, approaches for early diagnosis of bronchial lesions are critical for improving lung cancer patient treatment. Using bronchoscopy to image the airway epithelium during a regular airway exam is a noninvasive technique for clinicians to look for such lesions.
Autofluorescence bronchoscopy is one of the most sensitive advanced bronchoscopic video procedures available today. It can efficiently distinguish growing bronchial lesions from the normal epithelium. Unfortunately, the current standard requires human inspection of an incoming AFB video stream, which is time-consuming and error-prone
Continue reading| Check out the paper and github link
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https://text-generator.io now analyses not just linked images but also any text in them so you can analyse receipts/documents/screenshots etc.
Example: https://text-generator.io/playground?text=Checkout+this+reciept+https%3A%2F%2Fstatic.text-generator.io%2Fstatic%2Fimg%2Fcomputer-invoice.png+%0ATotal+Price%3A+&stop_sequences=&number_of_results=1&max_length=100&max_sentences=1&min_probability=0&top_p=0.9&top_k=40&temperature=0.6&repetition_penalty=1&seed=0
Will be a blog coming soon about it :)
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Editor’s Note: This post has been updated to reflect the XPENG G9 launch. It was originally published in November 2021. You don’t need a private plane to be at the forefront of personal travel. Electric automaker XPENG launched the G9 SUV this week during NVIDIA GTC. The intelligent, software-defined vehicle is built on the high-performance Read article >
The post An Elevated Experience: XPENG Launches G9 EV, Taking Innovation Even Higher with NVIDIA DRIVE Orin appeared first on NVIDIA Blog.
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The massive virtual worlds created by growing numbers of companies and creators could be more easily populated with a diverse array of 3D buildings, vehicles, characters and more — thanks to a new AI model from NVIDIA Research. Trained using only 2D images, NVIDIA GET3D generates 3D shapes with high-fidelity textures and complex geometric details. Read article >
The post World-Class: NVIDIA Research Builds AI Model to Populate Virtual Worlds With 3D Objects, Characters appeared first on NVIDIA Blog.
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This post is co-written by Goktug Cinar, Michael Binder, and Adrian Horvath from Bosch Center for Artificial Intelligence (BCAI). Revenue forecasting is a challenging yet crucial task for strategic business decisions and fiscal planning in most organizations. Often, revenue forecasting is manually performed by financial analysts and is both time consuming and subjective. Such manual […]
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In Part 7.0 of the Transfer Learning series we have discussed about Densenet pre-trained model in depth so in this series we will…
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The product of the industry 4.0 revolution is Internet connectivity, the widespread availability of robust wired and Wi-Fi networks, and…
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CHATBOTS IN BANKING AND FINANCIAL SECTOR: WHAT ARE THE CHALLENGES & OPPORTUNITIES?
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AI Weirdness: the strange side of machine learning
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Would love for this community to check it out and give us your feedback, it's 100% free to use and create an account: https://consensus.app/search/
You can ask any plain English research question and we will use language models to try to find relevant findings in research papers. Here's an example: Does Magnesium help with sleep?
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Hey guys! I ran a few benchmarks on Whisper's runtime and cost-to-run on GCP, so just dropping it here in case it's valuable to anyone!
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The goal of blind face restoration is to recover high-quality images of human faces from their low-quality counterparts that have been degraded for an unknown reason. Some degradation causes could be noise, blur, low-resolution, and compression artifacts. In this work, researchers from the Applied Research Center of the Tencent company propose GFP-GAN, a Generative Facial Prior GAN for real-world blind face restoration. As it is possible to see in Figure 1, the images restored through GFP-GAN reach higher realness and fidelity with fewer artifacts.
Continue reading | Check out the paper and github link.
https://preview.redd.it/vvss7n3lnhp91.png?width=1045&format=png&auto=webp&s=8fd0c5ffae078a9aae3ec978caacc898d050bd1a
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I've learned a lot about AI applications by using other people's Google Colab notebooks.
When OpenAI's Whisper arrived, I created a Google Colab notebook so you can run both the transcription and translation functions of this automatic speech recognition system.
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Hey everyone! I'm sure many of you know that OpenAI released Whisper yesterday- an open source speech recognition model with weights available.
Not sure if this is allowed, but I wrote a guide on how to run Whisper that also provides some benchmarks on accuracy, inference time, and cost. Let me know what you think :)
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Data-centric AI doesn't just stop with cleaning and preparing data for model training - there are rich insights to be gleaned from production data. By analyzing, segmenting, and selectively relabeling your production inference data, you can generate datasets for future model retraining. This talk will show you how you can use human-in-the-loop oversight to generate high-quality, labeled datasets using Label Studio from your prediction data for future model retraining.
Tune in to the Modzy Discord Server today at 12:30 EDT!
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Our planet faces a global extinction crisis. UN Report shows a staggering number of more than a million species feared to be on the path of extinction. The most common reasons for extinction include loss of habitat, poaching, and invasive species. Several wildlife conservation foundations, research scientists, volunteers, and anti-poaching rangers have been working tirelessly […]
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Amazon’s product search engine indexes billions of products, serves hundreds of millions of customers worldwide, and is one of the most heavily used services in the world. The Amazon Search team develops machine learning (ML) technology that powers the Amazon.com search engine and helps customers search effortlessly. To deliver a great customer experience and operate […]
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When it rains, it pours. And this GFN Thursday brings a downpour of news for GeForce NOW members. The Logitech G CLOUD is the latest gaming handheld device to support GeForce NOW, giving members a brand new way to keep the gaming going. But that’s not all: Portal with RTX joins GeForce NOW in November, Read article >
The post Go Hands On: Logitech G CLOUD Launches With Support for GeForce NOW appeared first on NVIDIA Blog.
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Autonomous vehicle sensors require the same rigorous testing and validation as the car itself, and one simulation platform is up to the task. Global tier-1 supplier Continental and software-defined lidar maker AEye announced this week at NVIDIA GTC that they will migrate their intelligent lidar sensor model into NVIDIA DRIVE Sim. The companies are the Read article >
The post Continental and AEye Join NVIDIA DRIVE Sim Sensor Ecosystem, Providing Rich Capabilities for AV Development appeared first on NVIDIA Blog.
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This blog explains step by step method to convert YOLO V7 PyTorch model to TensorFlow lite.
https://vikasojha894.medium.com/converting-yolo-v7-to-tensorflow-lite-for-mobile-deployment-ebc1103e8d1e
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Hi all, I want to present my new JupyterLab extension jupyter_app_launcher (https://github.com/trungleduc/jupyter_app_launcher). It is used to customize the JupyterLab launcher with a simple YAML file.
Demo
Users can add custom entries to the launcher to:
Open a predefined notebook or markdown file.
Render a notebook in dashboard mode
Open a notebook with Voila
Local/remote services like Plotly Dash or Streamlit
A live demo is available at https://mybinder.org/v2/gh/trungleduc/jupyter_app_launcher/main?urlpath=lab
Documentation: https://jupyter-app-launcher.readthedocs.io/
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My co-founder and I, a senior Amazon research scientist and AWS SDE respectively, launched Marqo a little over a week ago - a "tensor search" engine https://github.com/marqo-ai/marqo
Another project doing doing semantic search/dense retrieval. Why??
Semantic search using vectors does an amazing job when we look at sentences, or short paragraphs. Vectors also do well as an implementation for image search. Unfortunately, vector representations for video, long documents and other more complex data types perform poorly.
The reason isn't really to do with embeddings themselves not being good enough. If you asked a human to find the most relevant document to some search query given a list of long documents, an important question comes to mind - do we want the document that on average is most …
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Girl with a pearl earring, Cute Obama creature, Donald Trump, Boris Johnson, Totoro, Hello Kitty
Online demo: https://replicate.com/lambdal/text-to-pokemon
Code and details: https://github.com/LambdaLabsML/examples/tree/main/stable-diffusion-finetuning
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Earlier this year, Amazon Comprehend, a natural language processing (NLP) service that uses machine learning (ML) to discover insights from text, launched the Targeted Sentiment feature. With Targeted Sentiment, you can identify groups of mentions (co-reference groups) corresponding to a single real-world entity or attribute, provide the sentiment associated with each entity mention, and offer […]
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This post was co-written by Marius Cealera, Senior Partner Solutions Architect at AWS, Zdenko Estok, Cloud Architect at Accenture and Sakar Selimcan, Cloud Architect at Accenture. Machine learning (ML) is a high-stakes business priority, with companies spending $306 billion on ML applications in the past 3 years. According to Accenture, companies that scale ML across […]
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Every company, regardless of its size, wants to deliver the best products and services to its customers. To achieve this, companies want to understand industry trends and customer behavior, and optimize internal processes and data analyses on a routine basis. This is a crucial component of a company’s success. A very prominent part of the […]
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Amazon SageMaker Autopilot has added a new training mode that supports model ensembling powered by AutoGluon. Ensemble training mode in Autopilot trains several base models and combines their predictions using model stacking. For datasets less than 100 MB, ensemble training mode builds machine learning (ML) models with high accuracy quickly—up to eight times faster than […]
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As personal transportation becomes electrified and automated, time in the vehicle has begun to resemble that of a living space rather than a mind-numbing commute. Companies are creating innovative ways for drivers and passengers to make the most of this experience, using the flexibility and modularity of NVIDIA DRIVE IX. In-vehicle technology companies Cerence, Smart Read article >
The post Inside AI: NVIDIA DRIVE Ecosystem Creates Pioneering In-Cabin Features With NVIDIA DRIVE IX appeared first on NVIDIA Blog.
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Breakthroughs in centralized, high performance computing aren’t just opening up new functionality for autonomous driving, but for the in-vehicle experience as well. With the introduction of NVIDIA DRIVE Thor, automakers can build unified AI compute platforms that combine advanced driver-assistance systems and in-vehicle infotainment. The centralized NVIDIA DRIVE architecture supports novel features in the vehicle, Read article >
The post HARMAN to Deliver Immersive In-Vehicle Experience With NVIDIA DRIVE IX appeared first on NVIDIA Blog.
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Whether for virtual assistants, transcriptions or contact centers, voice AI services are turning words and conversations into bits and bytes of business magic. At GTC this week, NVIDIA announced new additions to NVIDIA Riva, a GPU-accelerated software development kit for building and deploying speech AI applications. Riva’s pretrained models are now offered in seven languages, Read article >
The post Now You’re Speaking My Language: NVIDIA Riva Sets New Bar for Fully Customizable Speech AI appeared first on NVIDIA Blog.
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Dentists get a bad rap. Dentists also get more people out of more aggravating pain than just about anyone. Which is why the more technology dentists have, the better. Overjet, a member of the NVIDIA Inception program for startups, is moving fast to bring AI to dentists’ offices. On this episode of the NVIDIA AI Read article >
The post A Podcast With Teeth: How Overjet Brings AI to Dentists’ Offices appeared first on NVIDIA Blog.
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By continuously monitoring a patient’s gait speed, the system can assess the condition’s severity between visits to the doctor’s office.
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Mayor’s youth employment program brought local high schoolers to MIT this summer.
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I started my marketing career at the end of the 2000s. At that time, the digital marketing landscape was scarce and full of uncharted…
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I'm curating a list of resources on Online Learning, Multi-Armed Bandits, RL Theory and Online Algorithms at:
https://sudeepraja.github.io/ResourceOnlineLearning/
Please send in your recommendations for helpful resources in these topics and related areas. I'll add resources on RL Theory and Online Algorithms soon.
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Here's a link to the post where we show how to pass model inputs and outputs directly to the model, which can significantly improve latency by bypassing the PCIe bus and and CPU memory entirely.
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https://gretel.ai/synthesize2023
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Website: https://moraluncertainty.mlsafety.org/
ML Systems often make real-world decisions that involve ethical considerations (modulating social media feeds, conversational AI agents or chatbots, etc). As ML systems automate more aspects of our lives, they should be able to identify moral ambiguity so that they are more likely to proceed cautiously or indicate an operator should intervene.
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From predicting how COVID-19 will spread, to anticipating geopolitical conflicts, using ML to help inform decision-makers could have far-reaching positive effects on the world. The objective of this competition is to train a model to answer forecasting questions using publicly available internet data. For more info visit the competition website.
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https://preview.redd.it/xpjae8s6txo91.jpg?width=2669&format=pjpg&auto=webp&s=497aa4aeed9925d40f7aeebb215605320c43eadc
I have collected here [1,2] almost all available solutions and ideas with codes shared by top performers in the past Kaggle competitions. This list gets updated as soon as a new competition finishes. It allows you to search over the Kaggle past competitions solutions and ideas.
Please share it with your friends.
[1] https://github.com/faridrashidi/kaggle-solutions
[2] https://farid.one/kaggle-solutions/
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After playing around with the Stable Diffusion source code a bit, I got the idea to use it for lossy image compression and it works even better than expected. Details and colab source code here:
https://matthias-buehlmann.medium.com/stable-diffusion-based-image-compresssion-6f1f0a399202?source=friends_link&sk=a7fb68522b16d9c48143626c84172366
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I'm curating a list of resources on Online Learning, Multi-Armed Bandits, RL Theory and Online Algorithms at:
https://sudeepraja.github.io/ResourceOnlineLearning/
Please send in your recommendations for helpful resources in these topics and related areas. I'll add resources on RL Theory and Online Algorithms soon.
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I made a Wordle environment and an algorithm for solving. After some time training, you can see it doing something sensible but I think tuning the rewards, environment or algorithm might make it perform better. Happy to take and merge pull requests if you want to work on it! :)
Link: https://github.com/s-sd/wordle-rl
Stars appreciated! ;)
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Amazon SageMaker Data Wrangler reduces the time that it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio, the first fully integrated development environment (IDE) for ML. With Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of […]
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Pharmaceutical companies seeking approval from regulatory agencies such as the US Food & Drug Administration (FDA) or Japanese Pharmaceuticals and Medical Devices Agency (PMDA) to sell their drugs on the market must submit evidence to prove that their drug is safe and effective for its intended use. A team of physicians, statisticians, chemists, pharmacologists, and […]
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Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. These algorithms and models can be used for both supervised and unsupervised learning. They can process various types of input data, including tabular, […]
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A data platform is an integrated set of technologies that collectively meet an organization’s end-to-end data needs. It enables the acquisition, storage, preparation, delivery, and governance of your data, as well as a security layer for users and applications.
The post Platform Technical Management – Data Engineering View appeared first on Data Science Central.
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The world is becoming increasingly complex - as highlighted in my first article here - but the concern isn’t only about being complex. Considering the ever-increasing speed of the state of complexity, we have entered the age of polycrisis.
The post Living in a Risk Society – Change, Perpetual Crisis, Comprehension, and Policy appeared first on Data Science Central.
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The problem of data violation is one of the most threatening issues of being on the internet. The ambiguity regarding the collection, usage, and sharing of our personal and sensitive information adds to the insecurity experienced by most consumers.
The post How CPRA Will Change the Face of US Businesses appeared first on Data Science Central.
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South Korea’s most popular AI voice assistant, GiGA Genie, converses with 8 million people each day. The AI-powered speaker from telecom company KT can control TVs, offer real-time traffic updates and complete a slew of other home-assistance tasks based on voice commands. It has mastered its conversational skills in the highly complex Korean language thanks Read article >
The post No Hang Ups With Hangul: KT Trains Smart Speakers, Customer Call Centers With NVIDIA AI appeared first on NVIDIA Blog.
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At GTC today, NVIDIA unveiled a number of updates to its DGX portfolio to power new breakthroughs in enterprise AI development. NVIDIA DGX H100 systems are now available for order. These infrastructure building blocks support NVIDIA’s full-stack enterprise AI solutions. With 32 petaflops of performance at FP8 precision, NVIDIA DGX H100 delivers a leap in Read article >
The post New NVIDIA DGX System Software and Infrastructure Solutions Supercharge Enterprise AI appeared first on NVIDIA Blog.
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New cloud services to support AI workflows and the launch of a new generation of GeForce RTX GPUs featured today in NVIDIA CEO Jensen Huang’s GTC keynote, which was packed with new systems, silicon, and software. “Computing is advancing at incredible speeds, the engine propelling this rocket is accelerated computing, and its fuel is AI,” Read article >
The post Keynote Wrap-Up: NVIDIA CEO Unveils Next-Gen RTX GPUs, AI Workflows in the Cloud appeared first on NVIDIA Blog.
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Meet Violet, an AI-powered customer service assistant ready to take your order. Unveiled this week at GTC, Violet is a cloud-based avatar that represents the latest evolution in avatar development through NVIDIA Omniverse Avatar Cloud Engine (ACE), a suite of cloud-native AI microservices that make it easier to build and deploy intelligent virtual assistants and Read article >
The post NVIDIA Omniverse ACE Enables Easier, Faster Deployment of Interactive Avatars appeared first on NVIDIA Blog.
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The latest release of NVIDIA Maxine is paving the way for real-time audio and video communications. Whether for a video conference, a call made to a customer service center, or a live stream, Maxine enables clear communications to enhance virtual interactions. NVIDIA Maxine is a suite of GPU-accelerated AI software development kits (SDKs) and cloud-native Read article >
The post New NVIDIA Maxine Cloud-Native Architecture Delivers Breakthrough Audio and Video Quality at Scale appeared first on NVIDIA Blog.
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Recommender systems, the economic engines of the internet, are getting a new turbocharger: the NVIDIA Grace Hopper Superchip. Every day, recommenders serve up trillions of search results, ads, products, music and news stories to billions of people. They’re among the most important AI models of our time because they’re incredibly effective at finding in the Read article >
The post Why the New NVIDIA Grace Hopper Superchip Is Ideal for Next-Gen Recommender Systems appeared first on NVIDIA Blog.
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Promising to help process images faster and more efficiently at a vast scale, NVIDIA introduced CV-CUDA, an open-source library for building accelerated end-to-end computer vision and image processing pipelines. The majority of internet traffic is video. Increasingly, this video will be augmented by AI special effects and computer graphics. To add to this complexity, fast-growing Read article >
The post NVIDIA Introduces Open-Source Project to Accelerate Computer Vision Cloud Applications appeared first on NVIDIA Blog.
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In her 18 years as a competitive figure skater, Bettina Heim learned to land a lutz with speed and grace. Now, armed with a Ph.D. in quantum computing, she’s helping Microsoft Azure Quantum carve out a position at the cutting edge of cloud services. “I’ve always been attracted to interesting problems and working hard to Read article >
The post Growing Range of Researchers, Scientists Adopt NVIDIA cuQuantum and QODA appeared first on NVIDIA Blog.
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Robotics developers can span global teams testing for navigation of environments, underscoring the importance of easy access to simulation software for quick input and iterations. At GTC today, NVIDIA founder and CEO Jensen Huang announced that the Isaac Sim robotics simulation platform is now available on the cloud. Developers will have three options to access Read article >
The post NVIDIA Robotics Software Jumps to the Cloud, Enabling Collaborative, Accelerated Development of Robots appeared first on NVIDIA Blog.
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Content creation is booming at an unprecedented rate. Whether it’s a 3D artist sculpting a beautiful piece of art or an aspiring influencer editing their next hit TikTok, more than 110 million professional and hobbyist artists worldwide are creating content on laptops and desktops.
The post Creativity Redefined: New GeForce RTX 40 Series GPUs and NVIDIA Studio Updates Accelerate AI Revolution appeared first on NVIDIA Blog.
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NVIDIA today introduced the NVIDIA IGX platform for medical edge AI use cases, bringing advanced security and safety to intelligent machines and human-machine collaboration. IGX is a hardware and software platform that delivers secure, low-latency AI inference to meet the clinical demand for instant insights from a range of devices and sensors for medical applications, Read article >
The post NVIDIA Medical Edge AI Computing Platform Selected by Top Robotic and Digital Surgery Startups appeared first on NVIDIA Blog.
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NVIDIA today introduced the IGX edge AI computing platform for secure, safe autonomous systems. IGX brings together hardware with programmable safety extensions, commercial operating-system support and powerful AI software — enabling organizations to safely and securely deliver AI in support of human-machine collaboration. The all-in-one platform enables next-level safety, security and perception for use cases Read article >
The post New NVIDIA IGX Platform Helps Create Safe, Autonomous Factories of the Future appeared first on NVIDIA Blog.
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Next-day packages. New vehicle deliveries. Fresh organic produce. Each of these modern conveniences is accelerated by fleets of mobile robots. NVIDIA today is announcing updates to Nova Orin — an autonomous mobile robot (AMR) reference platform — that advance its roadmap. We’re releasing details of three reference platform configurations. Two use a single Jetson AGX Read article >
The post NVIDIA Isaac Nova Orin Opens New Era of Innovation for Autonomous Mobile Robots appeared first on NVIDIA Blog.
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Deutsche Bahn’s rail network consists of 5,700 stations and 33,000 kilometers of track, making it the largest in Western Europe. Digitale Schiene Deutschland (Digital Rail for Germany, or DSD), part of Germany’s national railway operator Deutsche Bahn, is working to increase the network’s capacity without building new tracks. It’s striving to create a powerful railway Read article >
The post On Track: Digitale Schiene Deutschland Building Digital Twin of Rail Network in NVIDIA Omniverse appeared first on NVIDIA Blog.
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With tens of millions of weekly transactions across its more than 2,000 stores, Lowe’s helps customers achieve their home-improvement goals. Now, the Fortune 50 retailer is experimenting with high-tech methods to elevate both the associate and customer experience. Using NVIDIA Omniverse Enterprise to visualize and interact with a store’s digital data, Lowe’s is testing digital Read article >
The post Reinventing Retail: Lowe’s Teams With NVIDIA and Magic Leap to Create Interactive Store Digital Twins appeared first on NVIDIA Blog.
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With NVIDIA DRIVE, in-vehicle infotainment, or IVI, is so much more than just giving directions and playing music. NVIDIA founder and CEO Jensen Huang demonstrated the capabilities of a truly IVI experience during today’s GTC keynote. Using centralized, high-performance compute, the NVIDIA DRIVE Concierge platform spans traditional cockpit and cluster capabilities, as well as personalized, Read article >
The post Experience the Future of Vehicle Infotainment: NVIDIA DRIVE Concierge Brings Customized AI to Every Seat appeared first on NVIDIA Blog.
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The next generation of autonomous vehicle computing is improving performance and efficiency at the speed of light. During today’s GTC keynote, NVIDIA founder and CEO Jensen Huang unveiled DRIVE Thor, a superchip of epic proportions. The automotive-grade system-on-a-chip (SoC) is built on the latest CPU and GPU advances to deliver 2,000 teraflops of performance while Read article >
The post NVIDIA DRIVE Thor Strikes AI Performance Balance, Uniting AV and Cockpit on a Single Computer appeared first on NVIDIA Blog.
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Data science assists SEO experts in countless ways, like personalizing the customer experience, understanding client requirements, and many other things.
The post How to Use Data Science for Search Engine Optimization appeared first on Data Science Central.
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Hello! I wanted to share our recent work on understanding & explaining ML models through natural language conversations.
We use dialogues as an accesible tool for model understanding, so anyone can "talk" to an ML model to understand it, like its another colleague. We also provide a flexible implementation you can adapt to your models & datasets.
Twitter thread: https://twitter.com/dylanslack20/status/1571945003676737537
Paper: https://arxiv.org/abs/2207.04154
Code: https://github.com/dylan-slack/TalkToModel
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Yes, you read the title correctly.
This is more of a character study/shitpost testing out Stable Diffusion textual inversion to see how to control it / expected outputs. Turns out, it works better than I thought, and emphasizing/deemphasizing specific terms when using textual inversion works out well.
The post also includes a custom inference notebook for multiple inversion concepts.
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TorchStudio 0.9.10 was just released with extensions for all the major Python IDEs (VS Code, PyCharm, Spyder and Sublime Text) by popular request, looking forward for your comments !
One new tutorial and two new videos describe how to use TorchStudio from within your IDE.
Download: https://www.torchstudio.ai/download/Full changelog: https://github.com/TorchStudio/torchstudio/releases/tag/0.9.10
If you're new to TorchStudio, here's an introductory tutorial and video:
https://www.torchstudio.ai/getstarted/
https://www.youtube.com/watch?v=uvA-ARpKdCA
https://preview.redd.it/21tufwslnto91.png?width=3074&format=png&auto=webp&s=802b954254f44b5a737070b300c029457fe58962
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Video: https://youtu.be/xbxe-x6wvRw
Yannic Kilcher's summary: Stable Diffusion has been released and is riding a wave of creativity and collaboration. But not everyone is happy about this. This video takes a look at the vibrant open-source community around the model, and its critics.
Watch here: https://youtu.be/xbxe-x6wvRw
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I'm trying to do an excersive for my ML class, where I have to do lineal regresion with regularization, with either Lasso or Ridge.
Doing it with an iterative method, updating the weights, I have no idea how to actually do it.
Considering this are the augmented error measurements for Lasso and Ridge, I know I have to calculate the gradient, and (I think?) then the update rule becomes: w_new = w_old - (gradient of E_aug). But I'm not actually sure, and even more so, I wouldn't know how to compute the gradient itself, especially for Lasso.
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Last year, we announced the general availability of RStudio on Amazon SageMaker, the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE, and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) […]
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As AI becomes more deeply integrated into every aspect of our lives, it is essential that AI systems perform appropriately for their intended use. We know AI models can never be perfect, so how do we decide when AI performance is ‘good enough’ for use in a real life application? Is level of accuracy a […]
The post AI Models vs. AI Systems: Understanding Units of Performance Assessment appeared first on Microsoft Research.
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There have been startups that have survived, and there have been startups that have failed. However, what makes one startup succeed over…
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This youtuber is using some sort of ai character to talk for him im wondering what the software is called?
https://youtube.com/watch?v=GnVtXYvJveI&feature=share&si=EMSIkaIECMiOmarE6JChQQ
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It has annotated code of stable diffusion model; DDIM and DDPM sampling; and scripts to generate and in-paint.
- Code & notes: https://nn.labml.ai/diffusion/stable_diffusion/index.html
- Github: https://github.com/labmlai/annotated_deep_learning_paper_implementations
- This implementation based on the official implementation : https://github.com/CompVis/stable-diffusion
- We have deployed a server to try stable diffusion here: https://promptart.labml.ai
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In the blog “Why Data Management is Today’s Most Important Business Discipline”, I challenged the business and IT communities to reframe the data management conversation; to transform data management from an IT practice into a business discipline focused on leveraging data (and analytics) to deliver business and operational outcomes.
The post Data Management as a Business Discipline – Part 2: Theorems and Principles appeared first on Data Science Central.
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Algorithmic or automated trading refers to trading based on pre-determined instructions fed to a computer – the computers are programmed to execute buy or sell orders in response to varying market data. It’s a trading strategy widely adopted in the finance industry and still growing. The global algorithmic trading market is predicted to reach $18… Read More »How Algorithmic Trading Companies Automate Their Investment Strategy
The post How Algorithmic Trading Companies Automate Their Investment Strategy appeared first on Data Science Central.
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In this article, let’s discuss how data analysis in investment banking is transforming the way investment banks work, the challenges that they get when engaging in this transformation process, use cases, and more.
The post An Overview of Data Analytics in Investment Banking appeared first on Data Science Central.
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An even more significant challenge involves meeting the electrical demands of coming HPC systems and data centers in a sustainable way. Some exascale systems already have energy requirements akin to an entire town.
The post Making Data Centers More Sustainable appeared first on Data Science Central.
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Utah Governor Spencer J. Cox signed the Utah Consumer Privacy Act (UCPA) into law in March 2022. It has since become only the fourth US state to have its own data protection law after Colorado, Virginia, and California.
The post What Does Utah Consumer Privacy Act Mean for US Businesses? appeared first on Data Science Central.
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I'm trying to build a malicious URL detection algorithm using a hybrid DT and RF for my MSc dissertation and I'm having a bit of trouble implementing Stacking at the end of my code.
It currently works fine when using just DT and RF, but I'm really struggling to add the Stacking at the end for my final output. I've been trying to follow this, but it's not really working out.
You can see my code here and how I've been failing to add Stacking at the bottom.
I think the main area of issue is getting my dataset to work with the Stacking algorithm, I can't seem to translate it.
Can anyone please help me? This is driving me crazy
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Text annotations provide models with a better understanding of the data they are given, allowing them to interpret the text more accurately.
The post Usability of Text Annotation in Machine Learning appeared first on Data Science Central.
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